{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "602f6089-1591-4011-8307-9ee2cb064c67",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-03-14T02:31:03.794780Z",
     "iopub.status.busy": "2022-03-14T02:31:03.794151Z",
     "iopub.status.idle": "2022-03-14T02:31:04.134574Z",
     "shell.execute_reply": "2022-03-14T02:31:04.133936Z",
     "shell.execute_reply.started": "2022-03-14T02:31:03.794740Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### 点和线###\r\n",
    "import matplotlib.pyplot as plt\r\n",
    "x=9\r\n",
    "y=6\r\n",
    "plt.plot(x,y,'o')\r\n",
    "plt.show()\r\n",
    "\r\n",
    "x=[9,13]\r\n",
    "y=[6,10]\r\n",
    "plt.plot(x,y)\r\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "85976c8f-2e62-4ceb-a0f3-eb2ae13595ba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-03-14T03:06:59.972301Z",
     "iopub.status.busy": "2022-03-14T03:06:59.971159Z",
     "iopub.status.idle": "2022-03-14T03:06:59.996070Z",
     "shell.execute_reply": "2022-03-14T03:06:59.995006Z",
     "shell.execute_reply.started": "2022-03-14T03:06:59.972243Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'daye/line_animation.cvs'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_159/1536639776.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m###获取中国gdp数据\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0m小谭date\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"daye/line_animation.cvs\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0myear\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'time'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision)\u001b[0m\n\u001b[1;32m    686\u001b[0m     )\n\u001b[1;32m    687\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 688\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    689\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    690\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    452\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    453\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 454\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfp_or_buf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    455\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    456\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m    946\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    947\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 948\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    949\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    950\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m   1178\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"c\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1179\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"c\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1180\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1181\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1182\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"python\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m   2008\u001b[0m         \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"usecols\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0musecols\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2009\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2010\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2011\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munnamed_cols\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munnamed_cols\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2012\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'daye/line_animation.cvs'"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plot\r\n",
    "import pandas as pd\r\n",
    "###获取中国gdp数据\r\n",
    "小谭date=pd.read_csv(\"line_animation.cvs\")\r\n",
    "\r\n",
    "year=date['time']\r\n",
    "china=date['china']\r\n",
    "usa=date['usa']\r\n",
    "date.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c01b850e-158a-4737-bc89-c87d99bd637d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-03-14T03:11:03.720426Z",
     "iopub.status.busy": "2022-03-14T03:11:03.719609Z",
     "iopub.status.idle": "2022-03-14T03:11:03.741350Z",
     "shell.execute_reply": "2022-03-14T03:11:03.740523Z",
     "shell.execute_reply.started": "2022-03-14T03:11:03.720386Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: '../小谭date/line_animation.cvs'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_159/4003162075.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m###获取中国gdp数据\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"../小谭date/line_animation.cvs\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0myear\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'time'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision)\u001b[0m\n\u001b[1;32m    686\u001b[0m     )\n\u001b[1;32m    687\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 688\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    689\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    690\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    452\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    453\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 454\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfp_or_buf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    455\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    456\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m    946\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    947\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 948\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    949\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    950\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m   1178\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"c\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1179\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"c\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1180\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1181\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1182\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"python\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m   2008\u001b[0m         \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"usecols\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0musecols\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2009\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2010\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2011\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munnamed_cols\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munnamed_cols\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2012\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '../小谭date/line_animation.cvs'"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\r\n",
    "import pandas as pd\r\n",
    "###获取中国gdp数据\r\n",
    "data=pd.read_csv(\"../小谭date/line_animation.cvs\")\r\n",
    "\r\n",
    "year=data['time']\r\n",
    "china=data['china']\r\n",
    "usa=data['usa']\r\n",
    "data.describe()"
   ]
  }
 ],
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